CLWD: a Chinese histopathology dataset for lung adenocarcinoma subtype classification

Effective diagnosis and treatment of lung adenocarcinoma depends on accurate typing, subtyping, and grading. Herein, we present the CLWD dataset, a valuable resource for the lung cancer pathology community, comprising 408 whole-slide images (WSIs) from 210 patients specifically curated for the study of lung adenocarcinoma subtypes. Scanned at 80 × magnification, it is one of the largest datasets in Asia, with a particular emphasis on Chinese patient demographics. Notably, the dataset includes comprehensive clinical information, such as age, sex, and diagnosis, providing a robust foundation for diverse research needs. Publicly accessible, it supports a range of applications, including machine learning model development and validation. An initial evaluation of lung adenocarcinoma subtype classification using a multi-instance learning framework demonstrated that this dataset can substantially advance global research and improve the accuracy of subtype diagnosis.

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Publication Details

Journal
Scientific Data
Published
2026-03-05
DOI
https://doi.org/10.1038/s41597-026-06906-z
Primary Topic
Lung Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

CLWD: a Chinese histopathology dataset for lung adenocarcinoma subtype classification

Jun Ni, Dapeng Tao, Lei Li, Jubo Peng et al.
Scientific Data
Lung Cancer Diagnosis and Treatment
article

CLWD: a Chinese histopathology dataset for lung adenocarcinoma subtype classification

Jun Ni, Dapeng Tao, Lei Li, Jubo Peng, Peiren Tang, Ying Li, Haoyun Zhao, Yinghan Jiang, Li Wang, Jie Li, Rongsheng Liu, Yang Chen
article en

Abstract

Effective diagnosis and treatment of lung adenocarcinoma depends on accurate typing, subtyping, and grading. Herein, we present the CLWD dataset, a valuable resource for the lung cancer pathology community, comprising 408 whole-slide images (WSIs) from 210 patients specifically curated for the study of lung adenocarcinoma subtypes. Scanned at 80 × magnification, it is one of the largest datasets in Asia, with a particular emphasis on Chinese patient demographics. Notably, the dataset includes comprehensive clinical information, such as age, sex, and diagnosis, providing a robust foundation for diverse research needs. Publicly accessible, it supports a range of applications, including machine learning model development and validation. An initial evaluation of lung adenocarcinoma subtype classification using a multi-instance learning framework demonstrated that this dataset can substantially advance global research and improve the accuracy of subtype diagnosis.

Scientific Data
Yunnan University (CN), Kunming Medical University (CN), First People's Hospital of Yunnan Province (CN)
National Natural Science Foundation of China, Kunming Medical University, Kunming University of Science and Technology
Openalex Percentile: Top 32%
Lung Cancer Diagnosis and Treatment
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